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Aiming at the new coronavirus that appeared in 2019, which has caused a large number of infected patients worldwide due to its high contagiousness, in order to detect the source of infection in time and cut off the chain of transmission, we developed a new Chest X-ray (CXR) image classification algorithm with high accuracy, simple operation and fast processing for COVID-19. The algorithm is based on ConvNeXt pure convolutional neural network, we adjusted the network structure and loss function, added some new Data Augmentation methods and introduced attention mechanism. Compared with other classical convolutional neural network classification algorithms such as AlexNet, ResNet-34, ResNet-50, ResNet-101, ConvNeXt-tiny, ConvNeXt-small and ConvNeXt-base, the improved algorithm has better performance on COVID dataset.

Cervical cancer is a serious threat to women’s health. In recent years, the incidence rate has increased year by year, and the incidence of cervical cancer tends to be younger. Because of its characteristics of easy recurrence and easy metastasis, the drug therapy of cervical cancer has attracted increasing attention. Coixen ester has anti-cancer and immunomodulatory effects. After years of clinical research, it has been shown to be effective against a variety of cancers and has a growth inhibitory effect on tumor cells. This article aims to study the mechanism of Coixen ester-induced apoptosis of human cervical cancer HeLa cells. This article puts forward what are the causes of cervical cancer, and analyzes the positive effects of traditional Chinese medicine in the prevention and treatment of cervical cancer. During the experiment, the MTT method was used to study the effect of the complex on the proliferation of HeLa cells. The experimental results in this article show that a certain concentration of Coixen ester solution can inhibit cell proliferation and can also reduce cell viability to about 0.35.

Doxorubicin (DOX) is the most effective and extensively used treatment for many tumors. However, its clinical use is hampered by its cardiotoxicity. DOX-induced mitochondrial dysfunction, which causes reactive oxygen species (ROS) generation, cardiomyocyte death, bioenergetic failure, and decreased cardiac function, is a very important mechanism of cardiotoxicity. These cellular processes are all linked by mitochondrial sirtuins (SIRT3-SIRT4). Mitochondrial sirtuins preserve mitochondrial function by increasing mitochondrial metabolism, inhibiting ROS generation by activating the antioxidant enzyme manganese-dependent superoxide dismutase (MnSOD), decreasing apoptosis by activating the forkhead homeobox type O (FOXO) and P53 pathways, and increasing autophagy through AMP-activated protein kinase (AMPK)/mTOR signaling. Thus, sirtuins function at the control point of many mechanisms involved in DOX-induced cardiotoxicity. In this review, we focus on the role of mitochondrial sirtuins in mitochondrial biology and DOX-induced cardiotoxicity. A further aim is to highlight other mitochondrial processes, such as autophagy (mitophagy) and mitochondrial quality control (MQC), for which the effect of mitochondrial sirtuins on cardiotoxicity is unknown.

Atrial fibrillation (AF) is the most common cardiac arrhythmia with a high incidence of stroke. Many circular RNAs (circRNAs) have been demonstrated they are elated to various heart diseases and may play important roles in diagnostics or many pathophysiological processes. Nevertheless, there is Few studies on circRNAs functions in persistent AF. To identify AF-related circRNAs and construct the integrative regulatory network of circular RNAs, miRNAs, and mRNAs, we collected human right atrial appendage tissues from 5 patients suffering persistent AF (AF group) and 5 patients with normal sinus rhythm (NSR group) and characterized the global changes in circRNA expression with high-throughput sequencing technology. The differential expression of circRNAs and the interactions between circRNAs and microRNAs were analyzed. The microRNA expression file GSE68475 dataset was downloaded from the Gene Expression Omnibus (GEO) database to explore the differentially expressed microRNAs. The target genes of overlapped miRNAs were predicted by using DIANA-TarBase v8. We constructed the circRNA- miRNA-mRNA network using Cytoscape (version 3.4.0) and the network topology was analyzed by utilizing CentiScaPe app. Results showed that all of 600 differentially expressed circRNAs related to AF were screened, including 340 up-regulated and 260 down-regulated circRNAs. An integrative regulatory network was constructed, which included 30 circRNAs, 9 miRNAs and 130 target mRNAs of these miRNAs. It was concluded that that 30 circRNAs, including 8 upregulated circRNAs and 22 downregulated circRNAs, were predicted to highly possibly function as sponges of 9 miRNAs to regulate gene expression by using bioinformatics analysis. Moreover, the interactions of hsa-miR-339-5p with its related circRNAs and target mRNAs constructed the hub regulatory network in persistent AF by utilizing topology analysis. Our proposed regulatory network of circRNAs-miRNAs-mRNAs may provide new insight into the potential mechanism underlying persistent AF. Additionally, these important molecular may become novel biomarkers providing a new strategy in diagnosis and therapy of AF.

Two sample mean vectors comparison hypothesis testing problems often emerge in modern biostatistics. Many tests are proposed for detecting relatively dense signals with somewhat dense nonzero components in mean vectors differences. One kind of these tests is based on some quadratic forms about two sample mean vectors differences. Another kind of these tests is based on some quadratic forms about studentized version of two sample mean vectors differences. In this article, we propose a bootstrap test by adopting stationary bootstrap scheme to calculate p value of a typical test which is based on a quadratic form about studentized version of two sample mean vectors differences. Extensive simulations are conducted to compare performances of the bootstrap test with other existing typical tests. We also apply the bootstrap test to a real genetic data analysis about breast cancer.

A new control problem of roll-pitch seeker about the disturbance coupling is investigated in this work. Previous control strategies of roll-pitch seeker rarely considered the effects of the dynamic coupling disturbances from the missile angular motion, and because of the polar coordinate structure, the disturbance rejection strategies of yaw-pitch seeker cannot be utilized directly on roll-pitch seeker. Thus this article presents a new control strategy to improve the disturbance rejection ability of roll-pitch seeker. To analyze the disturbance coupling problem, the roll-pitch seeker model is derived with consideration of the missile body angular motion and torque disturbances. The motion equation of roll-pitch seeker shows that part of the dynamic coupling disturbance can be eliminated by certain choices of inertial parameters. The rest of disturbance is reduced by the stabilization loops using a differentiator-based disturbance compensation controller. Particularly, a missile body angular acceleration estimation method is designed for the compensator based on an adaptive differentiator. In addition, comparisons with other control strategies are carried out via numerical simulations, and the results confirm the effectiveness of the proposed method.

In the literature, a lot of work focused on studying intermittent control problems via feedback control strategy. No study on the intermittent control problems via sliding mode control method has been reported so far. This paper studies the problem of fast synchronization between two complex dynamical networks via aperiodically intermittent control and sliding mode control. In order to achieve fast synchronization of complex dynamical networks by using aperiodically intermittent sliding mode controller, new differential inequalities are derived firstly. After that, some sufficient finite-time synchronization criteria and finite-time achieving slide mode surface are obtained based on finite-time stability theory, aperiodically intermittent sliding mode control technique and constructing Lyapunov function. Finally, an example is provided to verify the effectiveness of the proposed theoretical methods.

Accurate prediction of load is very important in the management of power system. This paper proposed a two-stage optimization method of gray-Markov model with fractional order accumulation for shor...

Thermal infrared (TIR) object tracking is one of the most challenging tasks in computer vision. This paper proposes a robust TIR tracker based on the continuous correlation filters and adaptive feature fusion (RCCF-TIR). Firstly, the Efficient Convolution Operators (ECO) framework is selected to build the new tracker. Secondly, an optimized feature set for TIR tracking is adopted in the framework. Finally, a new strategy of feature fusion based on average peak-to-correlation energy (APCE) is employed. Experiments on the VOT-TIR2016 (Visual Object Tracking-TIR2016) and PTB-TIR (A Thermal Infrared Pedestrian Tracking Benchmark) dataset are carried out and the results indicate that the proposed RCCF-TIR tracker combines good accuracy and robustness, performs better than the state-of-the-art trackers and has the ability to handle various challenges.

In this paper, we studied a diffusive predator-prey model with competitive interference and Crowley-Martin type functional response. The conditions for local stability of coexisting equilibrium are given by analyzing the eigenvalue spectrum. By using delay as bifurcation parameter, conditions for occurrence of Hopf bifurcation are also given. The property of bifurcating period solutions is investigated by calculating the normal form. Some numerical simulations are performed to support our theoretical result. Our conclusions show that diffusion and delay are two factors that should be considered in establishing the predator-prey model, since they can induce spatially bifurcating period solutions.

At present, the one-stage detector based on the lightweight model can achieve real-time speed, but the detection performance is challenging. To enhance the discriminability and robustness of the model extraction features and improve the detector’s detection performance for small objects, we propose two modules in this work. First, we propose a receptive field enhancement method, referred to as adaptive receptive field fusion (ARFF). It enhances the model’s feature representation ability by adaptively learning the fusion weights of different receptive field branches in the receptive field module. Then, we propose an enhanced up-sampling (EU) module to reduce the information loss caused by up-sampling on the feature map. Finally, we assemble ARFF and EU modules on top of YOLO v3 to build a real-time, high-precision and lightweight object detection system referred to as the ARFF-EU network. We achieve a state-of-the-art speed and accuracy trade-off on both the Pascal VOC and MS COCO data sets, reporting 83.6% AP at 37.5 FPS and 42.5% AP at 33.7 FPS, respectively. The experimental results show that our proposed ARFF and EU modules improve the detection performance of the ARFF-EU network and achieve the development of advanced, very deep detectors while maintaining real-time speed.

Purpose: Nanomicelles (NMs) have been widely used for various biomedical applications due to its unique physiochemical properties. The present study aims to investigate the effects of vascular cell adhesion molecule-1 (VCAM-1)-targeted and peroxisome proliferator-activated receptor δ (PPARδ) agonist (GW0742)-loaded NMs on apoptosis and migration in oxidized low-density lipoprotein (ox-LDL)-induced human aortic vascular smooth muscle cells (HAVSMCs). Methods: The GW0742-loaded NMs (M-GW) and VCAM-1-targeted NMs loaded with GW0742 (TM-GW) were prepared, and then the morphologies and the size distribution of M-GM and TM-GM were observed by transmission electron microscopy (TEM) and dynamic light scattering (DLS), respectively. In vitro drug release assay of M-GM and TM-GM were performed as well. Next, HAVSMCs were cultured in medium containing ox-LDL to mimic atherosclerotic environment, and the effects of free GW0742, M-GM and TM-GM on endocytosis, cell migration and apoptosis, as well as the expression of VCAM-1, and proteins associated with migration and apoptosis were measured in HAVSMCs treated with ox-LDL. Results: M-GM and TM-GM were successfully prepared. VCAM-1 was overexpressed in HAVSMCs treated with ox-LDL, and TM-GM had a strong targeting ability to HAVSMCs treated with ox-LDL compared with M-GM. In addition, compared with free GW0742, both M-GM and TM-GM significantly diminished cell apoptosis and migration in HAVSMCs treated with ox-LDL. Conclusions: TM-GM had a superior suppressing effect on apoptosis and migration of ox-LDL-induced HAVSMCs.

Gravity and magnetic surveys are widely used in geology exploration because of its advantages, such as efficient and economy, green and environment-friendly, widely coverage and strong horizontal resolution. In order to well study in the geology exploration, it is required to comprehensively combine the different scales (different scales data) and different dimensions (satellite data, aeronautical data, ground data, ocean data, well data, etc.) of gravity and magnetic data that were observed in different periods, however, the comprehensive application of the multi-dimensional and multi-scale gravity and magnetic data still stays in the initial stage. In this paper, we do research on the key point of the fusion of potential field data (gravity and magnetic data): the way to fuse the different scales and different dimensions of potential field data into a benchmark and the same surface. Based on this research, we propose a scheme to fuse the multi-dimensional and multi-scale gravity and magnetic data. The synthetic models show that this fusion scheme is able to fuse the multi-dimensional and multi-scale gravity and magnetic data with great fusion results and small errors, in addition, the most important is that the fusion data conform to the characteristics of the potential field data and can meet the needs of data processing in the following steps. One of case studies in China has been accomplished to fuse aeronautical and ground gravity data that are different scales by using this fusion scheme. The fusion scheme we proposed in this study can be used in the fusion of the multi-dimensional (aeronautical, ground and ocean) and multi-scale gravity and magnetic data, which is good for interpretation and popularization.

Extracting text information in complex images is a hot spot in pattern recognition research with broad application prospects. Natural scene door numbers produce serious distortion due to blurred images, uneven illumination and low light illumination, which makes it difficult to achieve ideal results in character recognition, and recognizing characters of arbitrary length is even more of a challenge. In this paper, we adopt the improved Niblack’s local threshold segmentation method to segment the images, and mark the connected areas of the segmented images to highlight the important features, and finally input the above pre-processed images to the improved AlexNet network for target detection on SVHN (Street View House Number) to realize the detection of characters in real scenes. The experimental results show that the improved Alexet-based target detection method is able to complete the detection task of streetscape door number characters well with 92.89% correct recognition rate.

Three-dimensional (3D) digital images are helpful in studying the physical properties of a medium. Moreover, reconstructing a 3D image from a two-dimensional (2D) image via computer-mathematical modeling is an important process. Based on the relationship between cascaded grids, an ingenious cascaded polymorphic method is proposed in this work to reconstruct a 3D image from a 2D image. By using the cascaded polymorphic method, a patch can be copied directly into a reconstruction grid by matching the patterns between cascaded grids; the polymorphism of the templates correspond to the grid size. To improve the reconstruction performance further, the non-edge region expansion strategy for a layer and the non-edge region replication strategy for adjacent layers were also proposed. A core sample and building material were selected as the test materials, and several effective measurements were used as quantitative means. To display the reconstruction effect intuitively, 2D reconstruction experiments were also performed along with the 3D experiment. The results show that the reconstruction speed is significantly improved using the cascaded polymorphic method, and the morphological features of the 3D reconstruction are clearly promoted.

Weaning failure from mechanical ventilation is an important clinical problem, the traditional methods of assessing whether patients can be weaned from mechanical ventilation or not cannot meet the clinical needs. Finding more effective weaning indicators to determine the optimal timing of weaning has important clinical value for improving the outcome of weaning and reducing the mortality of patients. As a new method of assessing respiratory function of patients, electrical impedance tomography (EIT) is gradually applied to the clinic, and its guided assessment of respiratory function may open a new way for directing successful weaning. This article reviews the progress of EIT in ventilation weaning, in order to provide a new judgment method and theoretical basis for the successful weaning.

There are two main contributions in this paper: Firstly, by analyzing the frequency domain features and Mel domain features, we can identify footstep events and non-footstep events. Secondly, we compared the two footstep sound signals of the same person in frequency domain under different experimental conditions, finding that almost all of their peak frequencies and trough frequencies in the main frequency band are respectively corresponding one-to-one. However for the two different people, even under the same experimental conditions, it is difficult to have the same peak frequencies and trough frequencies in the main frequency band of their footstep sound signals. Therefore, this feature of footstep sound signals can be used to identify different people.

Metal-free halide materials have garnered significant attention. However, because of their large band gap, current metal-free materials are not suitable as solar cell absorbers. A metal-free semiconductor, DMEDA·I6, with a narrow band gap (∼1.36 eV) and strong light absorption, is a promising candidate for solar cell absorbers. Using the first-principles calculation method, a systematic investigation was conducted on the photovoltaic properties of DMEDA·I6, including electronic properties, variation trend of the band gap under strain, defect physics, and band alignments of solar cell interfaces. It was found that DMEDA·I6 crystallized in a one-dimensional I chain with alternating long and short I–I bond lengths. Although both the valence band maximum and conduction band minimum of DMEDA·I6 are derived from the I p states, their compositions are distinguishable owing to the abnormal I–I bond arrangement. The band gap of DMEDA·I6 increases when the lattice volume expands, which is similar to that of the popular lead-based perovskites and opposite to that of the conventional zincblende semiconductors. Among the intrinsic defects, only defect VI can produce a deep defect level in the band gap. The formation of VI can be suppressed under the I-rich preparation conditions; thus, I rich condition is proposed when preparing DMEDA·I6 solar cell absorbers. Commonly used hole transportation materials are suitable for DMEDA·I6-based solar cells, whereas electron transport materials (ETMs) with a lower lowest unoccupied molecular orbital than commonly used ETMs should be used.

The issue of toxicity and chemical stability are two concerns for organic–inorganic hybrid perovskites, impeding their further commercial applications. Double perovskite (CH3NH3)2SnI6 with a bandgap of 1.81 eV and stable chemical valence of Sn (+4) is considered as a promising alternative. By first-principles calculations, the electronic properties, defect physics, and interface engineering of the perovskite are investigated in this work. It is found that (i) MA2SnI6 has a direct bandgap with a large dispersion of a lower conduction band. Due to the direct I 5p–5p transition between band edges, the light absorption can be as high as 105 cm−1 in the visible range. (ii) An Sn rich and I poor condition is suggested when MA2SnI6 is used as an electron transporting material (ETM) because of its high n-type electronic conductivity. An Sn poor and I rich condition is proposed when MA2SnI6 is prepared for photovoltaic application, because it can suppress the formation of non-radiation centers. (iii) ICBA and Spiro are proposed to be suitable ETM and hole transporting material, respectively, in MA2SnI6 based solar cells.

Through first-principles calculations, the photovoltaic properties of Cs2PdI6 were investigated and found that (i) Cs2PdI6 has a quasi-direct band gap nature, and strong p–d coupling of lower conduction bands is responsible for light electrons; (ii) dominant Pdi and Ii defects would be produced at a deep level in the band gap which acts as charge trapping states. Thus, should be passivated by suitable external doping, if Cs2PdI6 works as a solar cell absorber; (iii) The Cs2Pd(I1-x Br x )6 alloy is highly miscible. Tunable band gap depending on composition x has a non-linear bowing behavior occurring a lowest band gap at composition Cs2Pd(I0.7Br0.3)6.

In order to obtain an overview of the gamma-ray bursts (GRBs), we need a full sample. In this paper, we collected 6289 GRBs (from GRB 910421 to GRB 160509A) from the literature, including prompt emission, afterglow and host galaxy properties. We hope to use this large sample to reveal the intrinsic properties of GRB. We have listed all the data in machine readable tables, including the properties of the GRBs, correlation coefficients and linear regression results of two arbitrary parameters, and linear regression results of any three parameters. These machine readable tables could be used as a data reservoir for further studies on the classifications or correlations. One may find some intrinsic properties from these statistical results. With this comprehensive table, it is possible to find relations between different parameters, and to classify the GRBs into different kinds of sub-groups. With the completion, it may reveal the nature of GRBs and may be used as tools like pseudo-redshift indicators, standard candles, etc. All the machine readable data and statistical results are available on the website of the journal., Comment: Comments welcome. The machine readable data and figure sets will be available in ApJS. The original collected data are available: https://drive.google.com/drive/folders/0B9pJKjl_EXbvcFNMYnQ0WVFLTjQ

The purpose of semantic segmentation is to classify the pixels within the target contour. Edge detection is another major basic vision task in machine vision. Today’s most effective semantic segmentation models and contour edge detection models are isolated networks. The edge of the output of the semantic segmentation model is coarse and cannot be directly used. And the output of the edge detection network cannot output the classification information of the pixels inside the contour. In view of the above shortcomings of the existing network, we propose a semantic segmentation model based on edge constraint optimization, so that the output of the semantic segmentation model has more delicate edge information, and the network directly outputs accurate contour edge graphs. The edge information output by the network can be directly used for tasks such as corner detection and center point detection. Experiments show that the mIOU statistics obtained by our model on the validation set of PASCAL VOC2012 can reach 83.9%. At the same time, more detailed edge details can be obtained. This algorithm has high engineering and theoretical research value.

This paper presents a solar tracking system based on ARM, which mainly adopts the solar trajectory tracking mode, supplemented by the photoelectric sensor tracking mode according to the weather condition, and control the motor rotation to achieve all-time accurate solar tracking. The experimental results show that, the system performance is reliable, and all-weather tracking accuracy is maintained within 0.15 degrees. Therefore, the system can be widely used in solar photovoltaic power generation and lighting devices with solar energy utilization ratio improving greatly.

To achieve higher detection rate and lower false alarm rate in dim and small target detection, this paper proposes a novel approach based on the Local Region Similarity Difference (LRSD). Then the regions where the true targets and suspected target areas exist in are extracted. To further eliminate the false target regions, we process the LRSD image with pipeline filter and then the true target is finally obtained. Experimental results on some real-life infrared (IR) images with different types of targets verify that the proposed method could effectively prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, experimental results demonstrate its superior and reliable detection performance by high detection rate and low false alarm rate.

In this paper, estimation of parameters in the extended growth curve model without assumption of normality is presented via outer product least squares for covariance (COPLS). The COPLS estimator for covariance can be explicitly expressed and proved to follow a linear transformation of k + 1 independent Wishart distributions for a normal error matrix, where k is the number of profiles of the growth curve. Then two-stage generalized least squares (GLS) estimators for regression coefficients are elaborately derived. Finally, the COPLS estimator and the two-stage GLS estimators are shown to have desired properties both in finite and large samples. Simulation studies for finite sample sizes are provided to confirm that the COPLS estimator and the two-stage GLS estimators are alternative competitors with some evident merits to the existing maximum likelihood estimators in small samples. A real data set is analyzed to demonstrate the proposed methodology.

This study compares three diameter distribution models to fit mixed-species forest stands using four example plots with two or three species components in Daxing'an Mountain, PR China. The methods include (1) a finite mixture model (FMM) to fit two or three species components simultaneously, (2) a single Weibull function to fit the whole plot only, and (3) a single Weibull function to fit each species component separately and the summation of the individual species produced the whole plot. Our results indicated that Method 2 is only suitable to regular and unimodal diameter distributions with a balanced reversed J-shape. Method 3 may be able to fit each species component well if its frequency distribution is known and available in the data. However, Method 3 ignores the interspecies relationships within a given plot. Thus, the summation of the species components may not produce a good fit for the whole plot. In contrast, Method 1 (FMM) fits the species component distributions simultaneously with the const...

This paper considers the estimating problem of a panel data partially linear model with spatial autoregressive errors and fixed effects. In addition, we allow the idiosyncratic errors to be intertemporally correlated. By combining the polynomial spline series approximation, the semiparametric least squares method and the difference based technique, a new generalized moment estimator for the autoregressive parameter of the spatial model is constructed. Its consistency and asymptotic normality are established. In order to avoid the incidental parameter problem, a difference based intertemporal covariance matrix estimator is proposed. Based on the estimated spatially and time-wise correlated error structure, we further construct a weighted difference based semiparametric least squares estimator (WDSLSE) and a weighted difference based polynomial spline series estimator (WDPSSE) for the parametric and nonparametric components of the mean model, respectively. We develop an asymptotic theory for these two estimators, including the asymptotic normality, asymptotic efficiency and convergence rate. In particular, we show that the parametric component estimator has the same asymptotic distribution as that based on completely known spatial autoregressive parameter and intertemporal covariance matrix. Simulation studies demonstrate that our asymptotic theory is applicable for finite samples, and the analysis of a real data set illustrates the usefulness of our developed methodology.

Roll-pitch gimballed infrared seeker has wide field of view but suffers from the rapid roll motion of the zenith-pass problem. For estimating the line-of-sight (LOS) rate with the roll-pitch seeker, we propose a coordinate transformation method to compensate for the impact of rapid roll motion. A precise LOS rate dynamics model is derived on the transformed coordinate system. And based on the model, we design a novel LOS rate estimator with the Improved Iterated Cubature Kalman Filter algorithm (IICKF). The proposed IICKF is derived from reducing the dimensionality of the optimization problem of the ICKF, which inherits the estimation accuracy but decreases the computational complexity of the algorithm. For validating, Monte Carlo simulations are performed at last. The simulation results show that the proposed LOS rate estimator outperform the standard EKF, CKF, ICKF, and can well cope with the rapid roll motion of the zenith-pass problem in roll-pitch gimballed infrared seeker system.

In this paper, we propose a framework of outer product least squares for covariance (COPLS) to directly estimate covariance in the growth curve model based on an analogy, between the outer product of a data vector and covariance of a random vector, and the ordinary least squares technique. The COPLS estimator of covariance has an explicit expression and is shown to have the following properties: (1) following a linear transformation of two independent Wishart distribution for a normal error matrix; (2) having asymptotic normality for a nonnormal error matrix; and (3) having unbiasedness and invariance under a linear transformation group. And, a corresponding two-stage generalized least squares (GLS) estimator for the regression coefficient matrix in the model is obtained and its asymptotic normality is investigated. Simulation studies confirm that the COPLS estimator and the two-stage GLS estimator of the regression coefficient matrix are satisfying competitors with some evident merits to the existing maximum likelihood estimator in finite samples.

This paper investigates estimation of parameters in a combination of the multivariate linear model and growth curve model, called a generalized GMANOVA model. Making analogy between the outer product of data vectors and covariance yields an approach to directly do least squares to covariance. An outer product least squares estimator of covariance (COPLS estimator) is obtained and its distribution is presented if a normal assumption is imposed on the error matrix. Based on the COPLS estimator, two-stage generalized least squares estimators of the regression coefficients are derived. In addition, asymptotic normalities of these estimators are investigated. Simulation studies have shown that the COPLS estimator and two-stage GLS estimators are alternative competitors with more efficiency in the sense of sample mean, standard deviations and mean of the variance estimates to the existing ML estimator in finite samples. An example of application is also illustrated.

A direct-current, atmospheric pressure, cold plasma microjet (PMJ) sustained in a quasi-steady gas cavity in liquid was used to inactivate Staphylococcus aureus suspended in distilled water. While helium gas (with 2% O 2 as additive) was used as working gas, an effective inactivation (>99%) was achieved in 6 min. The inactivation of bacteria was further verified by surface morphology examination and LIVE/ DEAD Baclight bacterial viability test (fluorescence microscopy). The overall pH and temperature of the liquid were monitored during the plasma treatment and were found to be below the critical values for the survival of S. aureus. Hydroxyl radical ( * OH) was detected via electron spin resonance (ESR) spectroscopy, and alongside other intermediate reactive species, is attributed to the effective inactivation of S. aureus. End-on optical emission spectroscopy show strong atomic oxygen emission both in air and in water.

Long-term robust tracking remains a challenging problem in visual object tracking. Based on the popular tracking-by-detection framework, we propose an approach named real-time long-term correlation tracking by single-shot multibox detection (RLCT-SSD), in which tracking and detection work in parallel and cooperate together. Our algorithm consists of two parts: a tracking module is expected to track in real time and accurately, whereas a detection module is responsible for verifying the tracking results at intervals, and redetecting if necessary. The detector updates the tracking module when the tracking result is unreliable. We introduce a motion model on the basis of fast discriminative scale space tracker to design our tracking module. The detection module is based on the single-shot multibox detector algorithm. To further reduce the computational cost, we use the ShuffleNet as our base network of detection. The experimental results on OTB2013 and OTB2015 demonstrate that our RLCT-SSD performs favorably against most state-of-the-art trackers and achieves long-term accurate tracking running in real time.

Objective A direct-current, cold atmospheric-pressure air plasma microjet (PMJ) was performed to inactivate Staphylococcus aureus (S. aureus) and Enterococcus faecalis (E. faecalis) in air. The process of sterilization and morphology of bacteria was observed. We wish to know the possible inactivation mechanisms of PMJ and explore a potential application in dental and other temperature sensitive treatment. Methods In this study, we employed a direct current, atmospheric pressure, cold air PMJ to inactivate bacterias. Scanning electron microscopy was employed to evaluate the morphology of S. aureus and showed rupture of cell walls after the plasma treatment and Optical emission spectrum (OES) were used to understand the possible inactivation mechanisms of PMJ. Results The inactivation rates could reach 100% in 5 min. When the distance between the exit nozzle of the PMJ device and Petri dish was extended from 1 cm to 3 cm, effective inactivation was also observed with a similar inactivation curve. Conclusion The inactivation of bacteria is attributed to the abundant reactive oxygen and nitrogen species, as well as ultroviolet radiation in the plasma. Different life spans and defensibilities of these killing agents may hold the key to understanding the different inactivation curves at different treatment distances.

A direct-current, cold-atmospheric-pressure air plasma microjet (PMJ) sustained in a quasi-steady gas cavity in a liquid medium is used to inactivate Staphylococcus aureus (S. aureus) suspended in the liquid. The temperature and the pH value of the liquid change to steady-state values of about 40 °C and 3.0–4.5, respectively, after 10 min of plasma treatment. The decrease in the pH is attributed to the reaction of NOx produced in the air plasma with water at the gas–liquid interface. The concentrations of NO and NO are measured to be 37 mg · L−1 and 21 mg · L−1, respectively, after a 20 min of plasma treatment. Effective inactivation of S. aureus is found to start after the pH values decreases to about 4.5. This is attributed to the high oxidizing potential of the perhydroxyl radical (HOO•) on the fatty acid in the cell membranes of the microorganisms in the liquid.

Objective To investigate the short-term and long-term therapeutic efficacy of preoperative intra-arterial infusion chemoembolization on stage IB2-IIB uterine cervix cancer (UCC).

The failure rate of the mixture of two normal distributions in an unequal variance case may have four changes in monotonicity. This work analyzes the conditions for which the four changes occur and others for which increasing failure rate and modified bathtub shape can be shown.